This pipeline is used to **extract the feature vector of the image**, first to normalize the image, and then use resnet50 model to generate the vector.
This pipeline is used to **extract the feature vector of the image**, first to normalize the image, and then to use the resnet50 model to generate the vector.
In fact, the pipeline runs by parsing [the yaml file](./image_embedding_resnet50.yaml), which declares some functions we call **Operator**, and the **DataFrame** required by each Operator. Next will introduce the interface, how to use it and how it works, have fun with it!
In fact, the pipeline runs by parsing [the yaml file](./image_embedding_resnet50.yaml), which declares some functions we call **Operator**, and the **DataFrame** required by each Operator. Next will introduce the interface, how to use it and how it works, have fun with it!
@ -66,4 +66,4 @@ This pipeline includes four functions: `_start_op`, `towhee/transform-image`, `t
Among the four Operator,`_start_op` and `_end_op` are required in any Pipeline, and they are used to start and end the pipeline in the Towhee system. For the other two Operators, please refer to [towhee/transform-image](https://hub.towhee.io/towhee/transform-image) and [towhee/resnet50-image-embedding](https://hub.towhee.io/towhee/resnet50-image-embedding).
Among the four Operator,`_start_op` and `_end_op` are required in any Pipeline, and they are used to start and end the pipeline in the Towhee system. For the other two Operators, please refer to [towhee/transform-image](https://hub.towhee.io/towhee/transform-image) and [towhee/resnet50-image-embedding](https://hub.towhee.io/towhee/resnet50-image-embedding).
